Initial basic proptest support for CooMatrix (missing tests)

nalgebra-sparse/Cargo.toml

@@ -4,6 +4,10 @@ version = "0.1.0"
 authors = [ "Andreas Longva", "Sébastien Crozet <developer@crozet.re>" ]
 edition = "2018"
 
+[features]
+proptest-support = ["proptest", "nalgebra/proptest"]
+
 [dependencies]
 nalgebra = { version="0.23", path = "../" }
 num-traits = { version = "0.2", default-features = false }
+proptest = { version = "0.10", optional = true }

nalgebra-sparse/src/lib.rs

@@ -81,6 +81,9 @@ pub mod csr;
 pub mod pattern;
 pub mod ops;
 
+#[cfg(feature = "proptest-support")]
+pub mod proptest;
+
 use std::error::Error;
 use std::fmt;
 

nalgebra-sparse/src/proptest.rs

@@ -0,0 +1,41 @@
+//! TODO
+//!
+//! TODO: Clarify that this module needs proptest-support feature
+
+use crate::coo::CooMatrix;
+use proptest::prelude::*;
+use proptest::collection::{SizeRange, vec};
+use nalgebra::Scalar;
+
+/// TODO
+pub fn coo<T>(
+                 value_strategy: T,
+                 rows: impl Strategy<Value=usize> + 'static,
+                 cols: impl Strategy<Value=usize> + 'static,
+                 max_nonzeros: usize) -> BoxedStrategy<CooMatrix<T::Value>>
+where
+    T: Strategy + Clone + 'static,
+    T::Value: Scalar,
+{
+    (rows, cols, (0 ..= max_nonzeros))
+        .prop_flat_map(move |(nrows, ncols, nnz)| {
+            // If the numbers of rows and columns are small in comparison with the
+            // max nnz, it will lead to small matrices essentially always turning out to be dense.
+            // To address this, we correct the nnz by computing the modulo with the
+            // maximum number of non-zeros (ignoring duplicates) we can have for
+            // the given dimensions.
+            // This way we can still generate very sparse matrices for small matrices.
+            let max_nnz = nrows * ncols;
+            let nnz = if max_nnz == 0 { 0 } else { nnz % max_nnz };
+            let row_index_strategy = if nrows > 0 { 0 .. nrows } else { 0 .. 1 };
+            let col_index_strategy = if ncols > 0 { 0 .. ncols } else { 0 .. 1 };
+            let row_indices = vec![row_index_strategy.clone(); nnz];
+            let col_indices = vec![col_index_strategy.clone(); nnz];
+            let values_strategy = vec![value_strategy.clone(); nnz];
+
+            (Just(nrows), Just(ncols), row_indices, col_indices, values_strategy)
+        }).prop_map(|(nrows, ncols, row_indices, col_indices, values)| {
+            CooMatrix::try_from_triplets(nrows, ncols, row_indices, col_indices, values)
+                .expect("We should always generate valid COO data.")
+        }).boxed()
+}